Environmental Erosion Research Journal

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Wind erosion is one of the natural disasters in the arid regions of central Iran is increasingly faced by mismanagement of natural resources in the rise of this phenomenon has had a large impact. Precipitation, temperature and wind are the most important climatic factors that affect this phenomenon. Lack of rainfall, temperature increased and wind speed increased evapotranspiration in the region is moving so knowing the parameters climate can be useful in the management of natural resources and agriculture. Damghan city is including areas prone to wind erosion phenomena in the North East of the country. The purpose of this study is climatic parameters (precipitation, temperature, evapotranspiration, wind) and the months of the dry zone and its impact on wind erosion. Based on the results of the mean daily temperature in the month of May to mid- October dry station cover dominates return, so once reaches of, July, August and September to its highest. Evapotranspiration rates are amount of rainfall over throughout the year, and the potential evapotranspiration to precipitation in the area is 11. In the months of May, June and July wind storm occurrences of cause and evapotranspiration over other months is also expressed in degrees month is greater than rainfall. In the months of August and September is more heat than any other month in the year of drought peak rainfall in the region is at its lowest. Thus the conditions for the occurrence of the phenomenon of wind erosion climatic factors examined in the region are possible. 

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The aim of this research is exploring the impact of changes in runoff and sediment of the upstream catchment on the changes in the area and amount of canopy in Gabric-Jask mangrove. Hence, hydro-climatological parameters including amount of precipitation, discharge, and sediment in Gabric catchment during the statistical period of 1993 to 2010 were selected and the annual standardized index related to each parameter respectively including SRI, SPI, and SSI were calculated. Also, satellite images of Landsat of TM and ETM⁺ sensors were used in order to explore the changes in the canopy by the use of NDVI and the area was prepared and its calculations were done. Cross correlation function and moving average of 3, 5, and 7 years were used to explore the relation between hydro-climatologic factors and the area and canopy of mangrove. Based on the results related to the canopy changes there was two increasing periods and one decreasing period and the area changes had an increasing trend during the study statistical period. Results of exploring the relation between incoming precipitation, discharge, and sediment to the mangrove forests show that NDVI changes and the area of mangrove forests have a significant relationship with three years moving average of SPI, SRI, and SSI indices with the correlation coefficients of 0.6, 0.8, and 0.56, respectively. Finally, results showed an increase in the rate of NDVI index with an amount of 0.33 and an increase in the area of Gabric-Jask mangrove forests with an amount of 0.22 ha/year.

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Extended abstract
 

1. Introduction

 
Topography is one of the effective factors in soil formation and development. Topographical features such as slope aspect and position, by affecting soil temperature, evaporation capacity, soil moisture content, soil organic matter, precipitation, movement, and accumulation of soil solution can impress soil microbial properties. For investigating the effect of land-use change on soil ecosystem functioning because of human activities, it is essential to study the soil processes in disparate land-use systems and to preserve and regenerate the capability of soil to deliver ecosystem services. This study aimed at evaluating the effect of slope aspect and position on soil microbial indices in rangeland and forest areas of Heyran neck.
 

1. Methodology

This experiment was accomplished as factorial on the basis of a randomized complete block design with three treatments containing land use (forest and rangeland), slope aspects (north and south), and three slope positions (shoulder, footslope, toeslope), and four repetitions in Heyran neck, one of the functions of Astara city in Guilan province. Totally, 48 disturbed soil samples were taken from forest and rangeland at two aspects and three slope positions. From soil biological indices, soil microbial population, soil basal, and substrate-induced respiration (BR and SIR), microbial biomass carbon (MBC), and microbial quotient (q_mic ) were measured. Soil microbial population was determined by the most probable number method (MPN method). The basal soil respiration was determined by placing 50g of soil in glass jars together with 10mL 0.05N NaOH in 20mL glass vials. All samples were incubated for 24h at 25 ± 1 ^oC, and the CO₂ that evolved and was trapped during the period was determined by titration of the NaOH with 0.1N HCl. Substrate-induced respiration was determined by measuring the CO₂ production from 50gr fresh soil. The soil samples included 1% glucose, were first placed in a glass jar. Then, an absorption bottle that was filled with 25ml of 0.1N NaOH was carefully put in the glass jar, and the glass jar was precisely sealed. The jar was then incubated at 25 ± 1 ^oC for 6h. The evolved CO₂ was trapped by NaOH and determined by titration of NaOH with 0.1N HCL. Microbial biomass carbon was estimated by the chloroform fumigation and extraction method. Microbial quotient was calculated by dividing microbial biomass carbon (MBC) with soil organic carbon (SOC). Data’s normality was assessed through Kolmogorov–Smirnov test. The analysis of variance and comparison of means by Duncan test and Pearson correlations were done using SPSS software. Figures were prepared using Excel software.
 
3-Results & Discussion
The results showed that the content of all biological parameters measured in the forest soils was significantly higher than in the rangeland soils. In both land uses and in all slope positions, the highest values of basal soil and substrate-induced respiration, microbial population, and microbial biomass carbon were measured in the north-facing slope. In the studied land uses and slope aspects, all biological indicators except the microbial quotient had the highest value in the shoulder position. In the south-facing slope, the content of microbial quotient in the toeslope position was measured more than in other positions. Still, there was no significant difference from the value of this index in the shoulder position. The highest value of microbial quotient (1.95 mgC_mic.g^-1C_org) was observed in the north-facing slope on the shoulder, which was not significantly different from the value of this index in the footslope and toeslope positions of north-facing slope and also the shoulder and toeslope of south-facing slope. In forest land use, the content of microbial quotient in both north-facing (1.91 mgC_mic.g^-1C_org) and south-facing (1.9 mgC_mic.g^-1C_org) slopes was almost equal, which was significantly different from its value in both slope aspect of rangeland. The correlation between all biological indices at the level of one percent probability was positive and significant. There was the highest correlation between basal soil and substrate-induced respiration (r=0.94**) as well as microbial biomass carbon and substrate-induced respiration (r =0. 89**).
 
4- Conclusions
Overall, the results of this study showed that biological indices are dependent largely on landscape and land use, and by affecting the structure of the microbial community, these factors can affect the properties of the soil and its development. Due to the significant role of microorganisms as an integral component in the soil ecosystem and the effect of this component on the physical, chemical and nutritional properties of this ecosystem, by providing suitable conditions for the good activity of these organisms, soil quality can be increased, and thus erosion will be reduced.

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1- Introduction
Due to the fact that coastlines have a large part of the world's population and many facilities are located along the coasts, shoreline changes can cause a lot of damage to coastal areas. Coastal changes can be caused by natural and human processes and factors; however, coastal processes are often under human activities, locally or globally. Natural processes can also be enhanced or accelerated by human activities. One of the beaches that has undergone many changes is the shores of the Caspian Sea. Fluctuations in the Caspian Sea are faster than other seas and lakes. The Caspian Sea has experienced several periods of extreme fluctuations in recent decades, and this has led to the shifting of the coastline in each period of alteration. The shores of the Caspian Sea have long been of interest to human societies and numerous activities have taken place along its shores. Changes in the water level of this lake have always changed the lives of the inhabitants of the Caspian Sea and have caused damages and in many cases have led to the relocation of settlements and facilities. Also, changes in the level of the Caspian Sea, in addition to the coastline, have had important effects on Anzali Wetland. Due to past fluctuations in the level of the Caspian Sea, this wetland has been affected by these fluctuations more than other coastal areas of the Caspian Sea. Due to the importance of the issue, in this study, the effects of fluctuations in the Caspian Sea level on the coastline and Anzali wetland have been investigated.
2- Methodology
In this study, in order to achieve the desired goals, from 1: 50000 topographic maps, 1: 100000 geological maps, digital model of 12.5 m altitude, Landsat satellite images as well as statistical information related to sea level changes and climate situation Area are used as research data. The instruments used in the research included ArcGIS (in order to prepare the desired maps), ENVI (in order to prepare the desired maps) and IDRISI (in order to analyze the changes that occurred in the coastline and Anzali wetland). Also in this study, LCM models (to analyze land use change information and identify changes in the coastline and Anzali wetland) and a combined model of fuzzy logic and AHP (to identify areas vulnerable to environmental hazards and also identify areas prone to the development of human activities) have been used. This research has been carried out in several stages in accordance with the intended objectives. In the first stage, based on the statistical information of Bandar Anzali metering station, changes in the Caspian Sea level have been evaluated. In the second stage, using Landsat images, the changes of Anzali wetland have been studied. In the third stage, using Landsat images, shoreline changes have been evaluated and in the fourth stage, the relationship between changes in sea level, Anzali Wetland and shoreline has been explored.
3- Results
In this study, in order to investigate the changes in the Caspian Sea level, information about the leveling station of Bandar Anzali during the years 1990 to 2020 has been used. The results of the evaluation of the changes indicate that the surface of the Caspian Sea has decreased by 51 cm during the study period. Also in this research, using Landsat satellite images, the changes of Anzali wetland have been studied. According to the results, Anzali Wetland has undergone many changes in recent years, to the extent that this wetland in 1990 was about 37.46 square kilometers (wetland water area), which in 1995 increased to 39.24 square kilometers. From this date onwards, the area of the wetland has been decreasing so that the area of the wetland has been reduced in 2000 to 38.59, in 2005 to 37, in 2010 to 35.17, in 2015 to 33.49 and in 2020 to 30.04 square kilometers. The results of the coastline study also indicate that the average shoreline change in the study area from 1990 to 2020 was about 135.4 meters. In fact, during this period of time, under the influence of various natural and human factors, the coastline of the region has experienced a reversal of 135.4 meters.
4- Discussion & Conclusions
Declining Caspian Sea level, along with its environmental effects, has caused changes in Anzali Wetland and the coastline. In fact, the declining trend of the Caspian Sea has caused the level of Anzali Wetland to decrease in accordance with this trend and, as a result, the area of the wetland has decreased to the extent that during a period of 30 years, 7.42 square kilometers of wetland area has decreased. This issue has shown a direct effect of sea level decline, although human factors have also played an important role in these changes. Also, the declining trend of the Caspian Sea surface has caused the coastline to regress more rapidly in the study area, so that during a period of 30 years, the coastline of the study area has receded by about 135 meters, part of which is the reason for the decrease in sea level. In addition to sea level changes, human factors have also played an important role in shoreline changes. According to the results, man-made areas have increased by about 20 square kilometers during the years 1990 to 2020; consequently, the increasing trend of population and physical development of Anzali city as well as the development of various infrastructures towards the coastline have caused a change in the coastline and the decline has intensified. Also, human factors have played an important role in the inflow and outflow of water of Anzali wetland, so in changing the size of Anzali wetland these human-related factors have also been effective. According to the mentioned cases, the fluctuations of the Caspian Sea along with human activities have been one of the factors affecting the status of the coastline and Anzali wetland.

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1. Introduction

By developing GIS and remote sensing technology, the widespread access possibility and local distribution of hydrological management parameters and variables have become practical. Runoff rainfall modeling is always an important and continuous need for practical issues in the fields of water resources evaluation, flood forecasting, engineering canals designing, and many other goals (Bone, 2001). Calculation of runoff-rainfall results has been made practical and operationalized by using GIS techniques and a distributed hydrological model. The WetSpa runoff-rainfall model is a hydrological-distribution model that was developed in Brussels in 1997 (Wange et al, 1997) and also, had been used in various research and executive projects by developing in various models. This hydrological model has the capability of performing simulations at the pixel level and because of this, it provides the possibility of using aerial and satellite images with accurate information measured at the basin level, which has a local distribution (Hooshyarypor at el, 1397). Due to the high uncertainties of hydrological parameters, the calibration model is one of the most important part of modeling whose optimization techniques are mainly are used for such purposes. There are various methods for optimization, sensitivity analysis, and also evaluation of uncertainty of models. Accordingly, this paper’s purpose is to calibrate the WetSpa hydrological model with a multi-objective optimization approach that uses the Social Spider Algorithm (SSA) and the Black Widow Spider (BWO) techniques. By this point of view, to achieve a reliable prediction, in addition to the usual discharges, the model must be able to predict high and low discharges accurately (including maximum and minimum), so the objective functions are selected in a way that the best match between observational and computational values can be achieved during the Vasanji process.

2. Materials and Methods
   1. WetSpa Model

WetSpa is a continuous local and temporal model in which all of the simulations are conducted continuously. The WetSpa model displays the water and energy balance for each calculation cell, considers rainfall processes, vegetation, snowmelt, wetting, infiltration, evapotranspiration, leakage, surface runoff, wall flow, and groundwater flow. The hydrological system simulated by this model consists of four layers: vegetation, soil surface, root zone, and saturated groundwater table.

1. 2. The Optimization algorithms

The Social Spider Optimization (SSO) algorithm is a new optimization approach which is proposed in 2013 by Kause et al. Another optimization approach used in this paper is the Black Widow Spider (BWO) optimization algorithm. During the day, the black widow spider is out of sight and is mostly nocturnal, and rotates its network during the night. Generally, the widow spends most of her adult life on the same site (Andrite and Banta, 2002).

1. 3. Objective functions and model evaluation

In this paper, to evaluate the model, five statistical indices have been used of correlation coefficient (r), Root Mean Square Error (RMSE), mean absolute error (MAE), Nash-Sutcliffe index, and Nash-Sutcliffe logarithmic index. To increase the accuracy of the model in predicting the minimum and maximum flows, two alogarithm Nash-Sutcliffe and Nash-Sutcliffe logarithmic criteria were used.

1. 4. Zashk basin and model data

Zashk Basin is located in Khorasan Razavi province and in the west of Mashhad with an area of 65.56 square kilometers.

3. Result and Discussion

In this part of the paper, the calibration results of the WetSpa model using social spider and black widow spider algorithms are presented. The problem decision variables are the 11 global parameters illustrated in Table 1. Objective functions must be selected in a way that at the end of the calibration process the best match between the observed and computational values can be obtained. Some of these functions give more weight in high flows, while others consider more weight in low flows and have more emphasis on them. In this regard, Nash-Sutcliffe (NS) criterion and its logarithmic form (NS-Log) have been used. In this paper, the results obtained based on these two functions are illustrated. After determining all the necessary local networks in basin modeling, precipitation, evaporation, temperature, and discharge information from 2009 to 2011 were used to calibrate the model and 2012 to 2014 data were used to validate the results. Each of the optimization algorithms was conducted with an initial population size of 100 people and over 100 generations (number of times the optimization model was executed). As it was observed, the answers obtained by BWO are better than the answers of SSO due to its higher NS values. According to the obtained results, NS and NS-Log values are generally from -2.3 to 0.75 and from -0.165 to -0.01, respectively. This problem illustrates that the calibrated model has been more successful in simulating low discharges. In fact, since the model has been executed continuously, the simulation results in 2008 are considered as the Warm-Up period.

4. Conclusion

This paper calibrated the WetSpa distributed rainfall-runoff model. To calibrate the model, two evolutionary optimization algorithms of social spider (SSO) and black widow spider (BWO) were used in the Zashk basin of Mashhad. The results obtained from the usage of the model in this basin illustrated the satisfactory capability of these algorithms in calibrating the WetSpa model. Comparing the results obtained from the SSO and BWO algorithms illustrated that in the multi-objective calibration problem, the BWO algorithm was slightly more successful than the SSO model. Also, the results indicated that the simulation quality of low discharges was higher than the high ones. The reason for this problem, firstly, can be due to the lower abundance of high discharges in the evaluated data set and secondly, the relatively slow response of the model to changes in hydrological conditions in flood conditions in the catchment basin, because the temporary groundwater storage coefficient (K5) allocated a large amount for itself that can directly affect the reduction of surface runoff. On the other hand, the weakness of the results in predicting some low discharges can be related to the optimal value of groundwater recession coefficient (K2), which has taken a small amount in the calibration process. The results of this study illustrated that the effect of the surface runoff coefficient on the model results is much greater than other parameters (about 36%).
 

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1- Introduction
Spatial changes in soil properties are significantly influenced by factors affecting soil formation such as topography. Topography can create different properties in the soil by affecting the spatial distribution of effective environmental parameters. Topographic features such as contour, slope direction by affecting soil temperature, evaporation capacity, soil moisture, soil organic matter, precipitation, movement and accumulation of soil solution can affect the biological properties of soil. Respiration of soil microorganisms is one of the most sensitive and important biological properties that can affect soil quality. To study the impact of land use change on soil ecosystem performance due to human activities, it is necessary to maintain and restore soil capacity to provide ecosystem services. The aim of this study was to investigate the effect of slope and height classes on soil microbial respiration in agricultural, rangeland and forest areas of Khanghah Namin village.
2- Methodology
In order to conduct this research, in the fall, samples of intact and untouched soil from the study area were prepared in 72 points by regular networking method with distances of about 200 meters. Common physical and chemical properties of soil including soil pH, electrical conductivity, equivalent total calcium carbonate, organic matter, soil texture (percentage of sand, silt and clay particles) and total porosity were measured. From soil biomarkers, basal microbial respiration and substrate-stimulated respiration were determined. Kriging geo statistical method was used to estimate and determine the spatial distribution and evaluate some soil properties as well as cumulative soil quality indicators. For this purpose, the geographical coordinates of each point of the GPS device were transferred to GIS software. After recording the data of the sampled points, the interpolation command was executed and the information of the non-sampled points was obtained. In order to explain the spatial similarity of the variables, the experimental variogram of the data was obtained using GS + statistical software and the best variogram model was selected according to the variogram information. Finally, the distribution map of soil biological indicators was extracted using GIS and Kriging geo statistical methods. The correlation between the measured and estimated values of soil biological properties was calculated and evaluated in SPSS19 statistical software. Experimental factors included three land uses (namely, agriculture, rangeland and forest), slope direction at two levels (north and south) and two elevations (<1580 <) in terms of significant mean difference in field moisture. Normalization of data was performed by Shapiro-Wilk (1965) test using SPSS19 software. Mean comparison was performed unpaired by T-Test using SPSS19 statistical software. Pearson correlation between soil microbial base respiration and substrate-stimulated respiration with other soil properties was obtained in SPSS19 software.
3- Results
The results of the descriptive statistics of the soil properties showed that most of the soils in the study area have a loam soil texture class. The pH value of the samples was in the range of 5.7.7, the percentage of organic carbon was 0.6.6 % and calcium carbonate value was from 0.67 % to 16.67 %. The maximum electrical conductivity (EC) was less than 2 ds/m of Siemens per meter, indicating the non-saline soils of the area. Also, the high levels of average microbial base respiratory and the substrate induced respiration were 1.21 and 7.5, respectively. High correlation between the properties of soil organic carbon percentage, porosity percentage, silt percentage, farm moisture percentage and soil pH with base microbial respiration and substrate induced respiration with clay, sand and electrical conductivity of the soil were not significant. The farm moisture had the highest hydraulic soil with the lowest correlation with microbial respiration. In general, the average base and substrate induced respiration was higher on the height contour (1580<). Also, both base and substrate induced respiration in accordance with elevation had a significant mean difference at 5 %. In the present study, the studied slope on the north and southern slopes on the base microbial respiration level at 5 % probability level and substrate induced respiration with the probability level of 1 % was significantly different. The highest amount of these indicators was measured on the northern slope of the area and the lowest in the south slope of the southern south slope located mostly in the center to the northeast of the area and the northern slopes in the southern and northern parts of the area. It is maintained that the cause can be attributed to the existence of heights and solar radiation on the southern slopes. To determine the distribution of soil biological indexes at the level of the study area, the distribution of the area's biological properties of the area was prepared by applying the Kriging method. The best model for drawing soil base respiration map was selected for substrate induced respiration with the largest soil bed based on the highest R2, the range of impact, the least RSS and the effect of the piece. The largest amount of soil respiration was observed by the base respiration and irritated respiration in the north and northeast of the area. It is also observed that as the height of the area increases from west to east, basic respiration is generally stimulated with a relatively increased trend. The results show that there is a significant correction in both characteristics of measured and estimated values ​​by the Kriging internalization method.
4- Discussion & Conclusions
In this study, the amount of basal and bed-stimulated respiration in forest lands was significantly higher than rangeland and agricultural lands. Between rangeland and agricultural uses, the amount of soil microbial respiration in agricultural lands was lower. Due to the fact that this area is a tourist destination and there are local livestock, this finding can be attributed to transportation, high human and livestock activity at lower altitudes, and agricultural and pasture use, which are more exposed to these activities. The microbial respiration values ​​in the northern direction of the slope were significantly higher than in the southern direction. The southern slopes received more solar energy than the northern slopes. Usually in the south-facing slopes, the number and activity of soil microbial community is low due to high temperature, low water, low porosity and adverse consequences due to inadequate vegetation. In addition, a significant mean difference was observed in the northern and southern directions of the slope. Also, the increase in altitude due to the relative increase in humidity and decrease in temperature led to an increase in microbial respiration. This issue can significantly affect the activity and respiration of soil microorganisms by affecting soil processes and its development as well as the amount of vegetation in the two slopes. According to the obtained results, it can be stated that the evaluation of biological properties that was discussed can play a prominent role in controlling the management factors in the area. Large changes in soil respiration indices are probably due to the high sensitivity of these properties to human factors such as tillage operations and the use of chemical fertilizers, which cause changes in soil surface uniformity. The zoning map of these two features also confirmed this. The results showed a logical correlation between soil microbial respiration and other characteristics that the existence of a correlation between soil properties indicates a strong relationship between them. Geo-statistical science in this study was able to estimate the properties well. The results of this study showed that in the studied area, biological indicators depend on the position of the landscape and land use, and these factors can affect the structure, development and evolution of soil by affecting the structure of the microbial community.
 

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1. Introduction

Coastal areas are highly vulnerable, because they are involved with both sea hydrodynamic processes and human activities. Coastal geomorphology is considered as a prominent way to analyze coastal processes. Paleontology researches demonstrate tens of meters fluctuation in water level of the Caspian Sea. The shores of the Caspian Sea have variable topography and land use including lowlands (estuaries of rivers, gulfs and progradation) and sandy uplands. There is a slight slope in lowlands which cause flooding of lands when the sea level rises and also increased piezometric level of coastal aquifers. One the most important issues which must be considered in future development planning of coastal areas, is a proper space between constructions and sea that let natural processes be done. In fact, to determine the potential to deal with coastal hazards, it is necessary to prepare a coastal vulnerability map and identify areas with high vulnerability potential and strengthen and determine management approaches to protect investigated beaches. The investigated region is a 93.4 kilometer coastline in three cities including Talesh, Rezvanshahr and Anzali.

2. Methodology

To identify the level of vulnerability of the coastal areas of Gilan province in relation to hydrodynamic issues, the use of effective geomorphological factors is one of the methods of evaluating the level of vulnerability of the coastal areas in dealing with these processes. In this research, four variables were used in the form of 12 sub criteria  , using the hierarchical analysis method, to achieve the vulnerability index of the coastal area of ​​Talesh to Anzali cities. According to the mentioned references and the purpose of the study, the desired variables include sea level changes, land topography, geomorphology and land use. Landsat satellite images, topographic maps 1:25000 and digital model of 12.5 meters height of the research area as well as SAGA, IDRISI, ENVI, DSAS and Arc GIS software were used for analysis.

3. Results

The highest influence coefficient belongs to the factor of sea eustatic changes and then to the geomorphology variable. The most vulnerable coasts are those in which there are regression (more than 50 meters), the least distance and the highest density of agricultural use, the greatest distance and the lowest density of construction use, the lowest height and the slowest slope and the direction of the slope towards the land, the lowest density and the greatest distance from estuaries of rivers. The least vulnerable coasts are those in which there are progradation, the greatest distance and the lowest density of agricultural use, the least distance and the highest density of construction use, the highest height and the steepest slope and the direction of the slope towards the sea, the highest density and the least distance from estuaries of rivers. The largest coastal area belongs to areas with high and very high vulnerability including coastal areas of Anzali, Rezvanshahr, Asalem and some regions of Talesh. The smallest coastal area belongs to areas with very low vulnerability including coastal areas of Leisar and Pareh Sar. Generally, the coasts with low vulnerability are those around the breakwater of Pareh Sar and also those strengthened by the land currents. Therefore 56.2 kilometers out of 93.4 kilometers (60 percent) of investigated area, require a special attention to determine management approaches to protect coasts, prevent coastal erosion and nourishing the beach.

4. Discussion & conclusions

According to eustatic changes of the sea, areas with high vulnerability have the most length (58 kilometers) which have more than 50 meters regression, and the least vulnerability belongs to coasts with progradation. The estuaries of rivers are one of the prominent geomorphic forms in the studied area. In the area, there are 12 main rivers leading to the Caspian Sea which carry a considerable amount of sediment to coastal areas. This nourishes the coasts around estuaries and reduces vulnerability of the area. The most vulnerability in this respect, belongs to coasts of Bandar Anzali and areas between the Cities of Leisar and Talesh. Height, slow slope and the direction of slopes towards the land are the vulnerable factors of the beach, because they cause flooding in lands when the sea level rises. In terms of topology, there are no good conditions for natural protection of the beach in all the investigated areas, except a few beaches around the village of Rostam Mahalleh, located between the cities of Talesh and Asalem. In the coasts which have been submerged over the past 45 years, the backshore land use, which is mainly agricultural land, has been pushed back. Despite same sea level changes, the changes of coastlines are different. So that the backshore agricultural areas have an over 50 meters regression, while backshore areas with human structures have been more stable. For example, the beach of Pareh Sar breakwater has progressed in past 45 years despite the advance of sea water during the years. Therefore, it can be stated that the backshores with agricultural areas are more vulnerable than areas containing constructions. In terms of land use factor, the most vulnerability belongs to the coasts of Leisar and Asalem.

 

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1- Introduction
Carbon dioxide is one of the main greenhouse gases that affect the world's air temperature. Small changes in the amount of carbon dioxide emissions from the soil have a significant effect on the concentration of this gas in the atmosphere. Soil respiration, the process that emits carbon dioxide from the soil to the atmosphere, is one of the most important carbon flows in the ecosystem and includes two components of heterotrophic respiration (microbial respiration) and autotrophic respiration (root respiration). Researchers measure the rate of soil respiration for every 10 degrees Celsius of temperature change with an index called temperature sensitivity of soil respiration (Q₁₀). The evidence shows that the Q₁₀ value of the soil is not constant and has a negative correlation with temperature and a positive correlation with soil moisture. Also, the amount of soil organic carbon, incubation temperature and the interaction of these two have a significant effect on soil organic carbon decomposition. Accordingly, this research measures the temperature sensitivity (Q₁₀) in soil under tea cultivation and investigates its relationship with some soil chemical characteristics and topographic indices.
2- Methodology
After surveying the east and west tea gardens in Guilan province in the north of Iran, 200 samples were taken at a depth of 0 to 40 cm. The experiments were conducted to determine Organic Carbon, Labile carbon, Bulk density, PH, Cation Exchange Capacity, Microbial Biomass and soil microbial respiration. To measure Q₁₀, two temperature treatments of 25 and 35 °C were used. Elevation, slope and aspect were obtained using a DEM map in ArcGIS 10.5 and other topographical indicators such as wetness index, slope length, relative slope position, catchment area, channel network base level, vertical distance to channel network, convergence index, profile curvature and plan curvature were extracted from DEM map in Saga GIS 2.1.0. Pearson correlation was used to investigate whether there is any relationship between soil temperature sensitivity with other soil properties. Then, principal component analysis (PCA) was performed to determine a minimal data set. All the statistical analyses were done with SPSS 24. Regression charts were also drawn using Excel software.
3- Results
The Q₁₀ values varied from 1.19 to 1.58. This index has the most negative correlation with organic carbon (-0.863), Labile carbon (-0.863), microbial biomass (-0.837), respiration at 25 °C (-0.831) and 35 °C (-0.8) at 1% level and negative correlation with elevation at 5% (-0.159). The principal component analysis showed that the first six components (PC1, PC2, PC3, PC4, PC5 and PC6) have special values of more than one and were able to describe 73% of the total variance. The first main component (PC1) describes 23.125% of the total variance and includes soil organic carbon, labile carbon, microbial biomass and Q₁₀ which have the highest factor loading in this component. The second one (PC2), which explains about 12.99% of the total variance, has the highest factor loading with the vertical distance to the channel network (0.880). The third component (PC3) explains about 12.22% of the total variance. In PC3, clay has the highest factor loading. In the fourth component catchment area, convergence profile and slope length have the highest factor loading, respectively. Finally, the fifth and the sixth components are related to the elevation, slope and plan curvature.
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4- Discussion & Conclusions
The highest positive factor loading is related to soil organic carbon (0.981). Therefore, the first main component can be "part of the role of organic carbon in microbial biomass, labile carbon and temperature sensitivity". The results showed that Q₁₀ has the highest negative correlation with soil microbial biomass and organic and labile carbon. In other words, the higher the soil organic and microbial biomass carbon, the lower the amount of Q₁₀. Also, the second component can be considered as topographic indicators related to the channel network. Topographic indices can be used very strongly to model making soil organic carbon. The third component is related to clay properties. Several studies have indicated that the amount of clay has a high relationship with cation exchange capacity and it is a good indicator to determine the quality of soil. According to the results, although the correlation between some characteristics obtained from soil topographical analysis can prove the possibility of using them as auxiliary variables in predicting soil organic carbon, this point should be taken into account that other factors also play a role in the process of soil formation and development.